PSYCH 403A1: Neuroimaging and Neurostimulation

University of Alberta - Fall 2025
Instructor: Kyle Mathewson

This repository contains course materials for PSYCH 403A1, covering historical, contemporary, developing, and future technologies in neuroimaging and neurostimulation from both engineering and data analysis perspectives.

🚀 Quick Start

Visit the Course Website for lectures, assignments, and complete course information.

📚 Course Materials

Syllabus - Course policies, grading, and schedule
Assignments - Weekly lab assignments with interactive notebooks
Final Project - Project options and timeline
Lectures - Lecture outlines and materials

🔬 Interactive Assignments

This course features hands-on assignments using real neuroimaging data. Each assignment includes an interactive Jupyter notebook that runs directly in your browser:

Assignment 1: EEG Data Loading and Filtering

What you'll learn:

Load EEG data in BIDS format
Apply digital filters to remove artifacts
Create publication-quality scientific plots
Calculate and interpret power spectral density

Three ways to complete assignments:

🌐 Browser (Recommended): Click the Binder badge above - runs entirely in your browser!
💻 Local: Download notebooks and run with Jupyter on your computer
👁️ Preview: View notebook structure before deciding how to complete it

🛠️ Technical Requirements

For Browser Use (Recommended):

Any modern web browser
Internet connection
No installation required!

For Local Use:

Python 3.8+
Jupyter Lab/Notebook
Required packages: pip install -r requirements.txt

🎯 Learning Objectives

Students will gain experience with:

EEG/MEG: Signal processing, artifact removal, ERPs, frequency analysis
fMRI: Preprocessing, activation mapping, connectivity analysis
fNIRS: Optical brain imaging, hemodynamic responses
Neurostimulation: tDCS, TMS protocol design and safety
Programming: Python/MATLAB for neuroimaging analysis
Hardware: Understanding equipment from engineering perspective

📊 Equipment & Resources

25 portable EEG systems (Muse headsets)
Campus MRI facility access
Cutting-edge fNIRS system
tDCS and TMS equipment
Electronics lab with 3D printing
High-performance computing resources

🤝 Open Science & Collaboration

This course embraces open science principles:

✅ Open source tools (Python, MNE, Jupyter)
✅ Public datasets (OpenNeuro, PhysioNet)
✅ Reproducible research practices
✅ Version-controlled assignments
✅ No proprietary software dependencies

📞 Support

Instructor: Kyle Mathewson - kmathews@ualberta.ca
TAs: Tamari Shalamberidze - shalambe@ualberta.ca
Discord: Course Discussion
Office Hours: By appointment

📜 License

Course materials are available under open licenses where applicable. Please respect copyright for external resources and datasets.

Ready to explore the brain? Start with Assignment 1! 🧠✨

kylemath/NeuroimagingClass